{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "898db697-6d49-4bae-9e91-e32f2132d38b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "^C\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: jieba in d:\\anaconda\\lib\\site-packages (0.42.1)\n"
     ]
    }
   ],
   "source": [
    "pip install jieba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ffd57f3c-6abe-4741-8244-f83f93b0e6ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import jieba  \n",
    "import pandas as pd  \n",
    "import matplotlib.pyplot as plt  \n",
    "  \n",
    "# 设置matplotlib参数以确保中文和负号正常显示  \n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]  \n",
    "plt.rcParams[\"axes.unicode_minus\"] = False  \n",
    "  \n",
    "# 从网页读取HTML表格并保存到CSV文件  \n",
    "df = pd.read_html(\"https://www.air-level.com/rank\", encoding='utf-8', header=0)[0]  \n",
    "df.to_csv(\"PD.text+pd.xls.csv\", index=False)  \n",
    "  \n",
    "# 从CSV文件读取数据到DataFrame  \n",
    "dataframe = pd.read_csv('PD.text+pd.xls.csv')  \n",
    "  \n",
    "# 提取数据到列表  \n",
    "data = dataframe.values.tolist()  \n",
    "data1 = [item[1] for item in data]  # 使用列表推导式提取城市名称  \n",
    "data2 = [item[2] for item in data]  # 使用列表推导式提取AQI值  \n",
    "  \n",
    "# 定义颜色列表  \n",
    "color_list = ['k', 'm', 'b', 'r', 'c', 'w']  \n",
    "  \n",
    "# 绘制条形图  \n",
    "bar_width = 0.2  \n",
    "plt.figure()  \n",
    "plt.subplot(1, 1, 1)  \n",
    "x = data1  \n",
    "height = data2  \n",
    "for i in range(len(data)):  \n",
    "    if height[i] >= 301:  \n",
    "        plt.bar(x[i], height[i], width=bar_width, color=color_list[0])  \n",
    "    elif height[i] >= 201:  \n",
    "        plt.bar(x[i], height[i], width=bar_width, color=color_list[1])  \n",
    "    elif height[i] >= 151:  \n",
    "        plt.bar(x[i], height[i], width=bar_width, color=color_list[2])  \n",
    "    elif height[i] >= 101:  \n",
    "        plt.bar(x[i], height[i], width=bar_width, color=color_list[3])  \n",
    "    elif height[i] >= 51:  \n",
    "        plt.bar(x[i], height[i], width=bar_width, color=color_list[4])  \n",
    "    else:  \n",
    "        plt.bar(x[i], height[i], width=bar_width, color=color_list[5])  \n",
    "  \n",
    "# 设置图形标题和坐标轴标签  \n",
    "plt.title('城市空气质量')  \n",
    "plt.xlabel('城市')  \n",
    "plt.ylabel('AQI')  \n",
    "  \n",
    "# 在条形图上添加数值标签  \n",
    "for a, b in zip(x, height):  \n",
    "    plt.text(a, b, b, ha='center', va='bottom')  \n",
    "  \n",
    "# 显示图形  \n",
    "plt.show()  \n",
    "  \n",
    "# 将DataFrame保存到Excel文件  \n",
    "dataframe.to_excel(\"城市空气质量.xlsx\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbc81d32-6ee1-458f-a9ad-5b3d20048f92",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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